Paper Info
Title
Predicting the next location change and time of change for mobile phone users
Abstract
Predicting the next location of people from their mobile phone logs has become an active research area. Due to two main reasons this problem is very challenging: the log data is very large and there are variety of granularity levels for specifying the spatial and the temporal attributes. In this work, we focus on predicting the next location change of the user and when this change occurs. Our method has two steps, namely clustering the spatial data into larger regions and grouping temporal data into time intervals to get higher granularity levels, and then, applying sequential pattern mining technique to extract frequent movement patterns to predict the change of the region of the user and its time frame. We have validated our results with real data obtained from one of the largest mobile phone operators in Turkey. Our results are very encouraging, and we have obtained very high accuracy results.
Year
DOI
Venue
2014
10.1145/2675316.2675318
MobiGIS
Keywords
Field
DocType
algorithms,location prediction,data mining,sequential pattern mining,mobile phone users
Spatial analysis,Data mining,Time frame,Computer science,Temporal database,Operator (computer programming),Artificial intelligence,Granularity,Mobile phone,Cluster analysis,Sequential Pattern Mining,Machine learning
Conference
Citations 
PageRank 
References 
2
0.43
11
Authors
5
Name
Order
Citations
PageRank
Mert Ozer1445.85
Ilkcan Keles2254.39
Ismail Hakki Toroslu3456102.80
Pinar Karagoz415428.34
Salih Ergüt536519.17